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Fault Prediction Modeling for the Prediction of Number of Software Faults (SpringerBriefs in Computer Science) - Softcover
Inhaltsangabe
This book addresses software faults-a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.
A must-read for readers seeking a "one-stop" source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments.
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Über die Autorin bzw. den Autor
Dr. Santosh Singh Rathore is currently working as an Assistant Professor at the Department of Computer Science and Engineering, National Institute of Technology (NIT) Jalandhar, India. He received his Ph.D. degree from the Indian Institute of Technology Roorkee (IIT) and his master’s degree (M.Tech.) from the Indian Institute of Information Technology Design and Manufacturing (IIITDM) in Jabalpur, India. His research interests include Software Fault Prediction, Software Quality Assurance, Empirical Software Engineering, Object-Oriented Software Development, and Object-Oriented Metrics. He has published in various peer-reviewed journals and international conference proceedings.
Dr. Sandeep Kumar is currently working as an Assistant Professor at the Department of Computer Science and Engineering, Indian Institute of Technology (IIT) Roorkee, India. His areas of interest include Semantic Web, Web Services, and Software Engineering. He is currently engaged in various national and international research/consultancy projects and has many accolades to his credit, e.g. a Young Faculty Research Fellowship from the MeitY (Govt. of India), NSF/TCPP early adopter award―2014, 2015, ITS Travel Award 2011 and 2013, etc. He is a member of the ACM and senior member of the IEEE. His name has also been listed in major directories such as Marquis Who’s Who, IBC, and others.
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This book addresses software faults—a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.
A must-read for readers seeking a “one-stop” source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments.
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- VerlagSpringer
- Erscheinungsdatum2019
- ISBN 10 981137130X
- ISBN 13 9789811371301
- EinbandTapa blanda
- SpracheEnglisch
- Auflage1
- Anzahl der Seiten92
- Kontakt zum HerstellerNicht verfügbar
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Fault Prediction Modeling for the Prediction of Number of Software Faults
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Springer Nature Singapore, 2019
ISBN 10: 981137130X
ISBN 13: 9789811371301
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Fault Prediction Modeling for the Prediction of Number of Software Faults
ISBN 10: 981137130X
ISBN 13: 9789811371301
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Taschenbuch. Zustand: Neu. Neuware -This book addresses software faults¿a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 92 pp. Englisch. Artikel-Nr. 9789811371301
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Fault Prediction Modeling for the Prediction of Number of Software Faults
Verlag:
Springer Nature Singapore, Springer Nature Singapore, 2019
ISBN 10: 981137130X
ISBN 13: 9789811371301
Neu
Taschenbuch
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book addresses software faults-a critical issue that not only reduces the quality of software, but also increases their development costs. Various models for predicting the fault-proneness of software systems have been proposed; however, most of them provide inadequate information, limiting their effectiveness. This book focuses on the prediction of number of faults in software modules, and provides readers with essential insights into the generalized architecture, different techniques, and state-of-the art literature. In addition, it covers various software fault datasets and issues that crop up when predicting number of faults.A must-read for readers seeking a 'one-stop' source of information on software fault prediction and recent research trends, the book will especially benefit those interested in pursuing research in this area. At the same time, it will provide experienced researchers with a valuable summary of the latest developments. Artikel-Nr. 9789811371301
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